Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

• Published in: OR Spectrum Vol. 44; no. 4; pp. 1213 - 1254
• Main Authors: Hatami-Marbini, Adel, Arabmaldar, Aliasghar, Asu, John Otu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2022; Springer Nature B.V
• Subjects: Business and Management; Calculus of Variations and Optimal Control; Optimization; Data envelopment analysis; Decision making; Efficiency; Empirical analysis; Operations Research/Decision Theory; Optimization; Original; Original Article; Petroleum industry; Petroleum refineries; Productivity; Refineries; Robustness; Uncertainty; United States > US; Undesirable output; Productivity growth; Robust optimisation; Data envelopment analysis; Oil refinery
• ISSN: 0171-6468; 1436-6304
• DOI: 10.1007/s00291-022-00683-y

This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multiple resources and multiple outputs. This study first develops a unique framework based upon data envelopment analysis (DEA) to measure efficiency and productivity in the way that it tackles the uncertainty in data and undesirable outputs and, in turn, provides useful information to decision-makers. An adaptive robust optimisation is utilised to combat uncertain data whose distributions are unknown and consider the nexus between the level of conservatism and decision-makers’ risk preference. The key advantage of the proposed robust DEA approach is that the results remain relatively unchanged when uncertain conditions exist in the problem. An empirical study on the oil refinery is presented in situations of data uncertainty along with considering CO 2 emissions as the undesirable output to conduct environmental efficiency and productivity analysis of the 25 countries over the period 2000–2018. The empirical results obtained from the proposed approach give some imperative implications. First, results show that the price of robustness does not affect identically for varying technologies when assessing productivity in a global oil market, and the USA oil industry is observed as the highest productivity growth in all cases confirming its efforts for the rapid rise in oil extraction and production at low costs. There may be practical lessons for other nations to learn from the USA oil industry to improve productivity. Findings also support a considerable regress during the 2008 Global Financial Crisis in the oil industry compared to the rest of the periods in question, and due to monetary and fiscal stimulus, there is a sharp productivity growth from 2009 to 2011. The other implication that can be drawn is that the GDP growth rate and technology innovation can more effectively improve the productivity of the oil industry across the globe.